Increasing Throughput by Run Time Reduction Leads to Greater Efficiency in Juice Laboratory

This application note demonstrates to provide rapid analysis for the detection and confirmation of polyphenolic compounds in fruit juices, and increase productivity through the QC use of UPLC-MS analysis.

Phenolic compounds widely exist in many fruits and vegetables and are reported to have a diverse range of health benefits.^1,2,3,4 Their presence in food and beverages help contribute to the flavor, stability, nutrition, acceptability, and quality — all important aspects for successful products in a competitive marketplace.

Today, consumers expect manufacturers and retailers to supply wholesome and authentic fruit juices. Manufacturers must satisfy both consumer and regulatory requirements by providing products that are diverse in their flavor offerings and also meet any relevant compliance standards for quality and safety. Ultimately this allows the manufacturer to protect and strengthen their brand image in a highly competitive market place.

These factors highlight the need for reliable, robust techniques that can authenticate the purity of fruit juices and guarantee product quality. Often, a variety of fruits can have a similar physical appearance, for example apples and pears. This may result in the incorrect mixture of juices during processing. By monitoring key compounds with analytical techniques, the presence of unlabeled fruits in a given product can be detected.

For decades, reversed phase chromatography has been used to separate and identify polyphenolic compounds in a variety of sample matrices. While methods have been developed to examine polyphenolic content, the run times for these analyses are often long (60 - 100 minutes^1,2,3,4,5) and they create bottlenecks within the QC laboratory.

For a QC lab, the demands to improve productivity and reduce costs are two key areas that must are assessed by lab managers.

This application note describes a rapid method for the chromatographic fingerprinting of fruit juices and the quantification by MS of key polyphenolic compounds in commercial fruit juices.

Two methods were developed for the analysis of polyphenols in the QC laboratory. The first (Method 1) is suitable for chromatographic fingerprinting. This has the advantage of increased resolution, which is suitable for either UV (qualification/chromatographic fingerprinting, and quantification) or MS detection (quantification and confirmation of unknowns).

The second method (Method 2) is dedicated to the quantification of the key compounds that have already been identified as markers for adulteration in fresh fruit beverages. This method uses MS detection to quantify these components utilizing its increased selectivity compared with UV single wavelength monitoring.

Sample Preparation

Each sample was diluted with water:methanol (75:25) and filtered through a 0.45 μm filter.

ACQUITY TUV Conditions

The UV chromatogram was used to obtain a chromatographic fingerprint for each of the samples analyzed.

Wavelengths: 280 nm and 305 nm.

For Method 1, full scan was selected for the mass spectrometer so that the information from the detector could be used to identify unknown peaks of interest.

For Method 2, SIR mode was selected for the mass spectrometer and the conditions were optimized for each compound using Waters IntelliStart Software.

Current methods that involve the analysis of polyphenols require long run times that often are greater than 60 minutes per sample. The aim of this experiment was to transfer an existing HPLC method requiring 90 minutes per sample, to the ACQUITY UPLC System to improve productivity in the lab.

Various fruit juices were chosen for the analysis of polyphenolic content: apple, pear, peach, orange, and tangerine. For both methods 11 compounds listed in Table 1 were monitored and quantified during the analysis. During QC analysis, the presence or absence of these compounds was monitored along with the amounts at which they are present.

Figure 1 shows a typical chromatogram of a tangerine sample using HPLC and UPLC.

The ACQUITY UPLC System, in combination with 1.8 μm particle size columns were used to achieve increased resolution (as seen in Figure 1b) and rapid run times — the 100 minute run time was reduced to less than 25 minutes.

The reduction in run time also enables an increase in throughput for this analysis. The potential throughput increase for this method can be seen in Table 2.

Table 3 shows, the ACQUITY UPLC shows the potential cost savings that a laboratory can achieve by transferring from HPLC to UPLC technology.

In order to achieve the increased analysis speed and improved peak resolution, both methods were run using optimal UPLC flow rates for a 1.8 μm column (between 0.45-1.05 mL/min: as specified by the Van Deemter curve¹). By running the ACQUITY UPLC System between these flow rates (which in turn will produce elevated pressures due to the small particle size), maximum results for the system will be returned.

For Method 1, the throughput tripled. It can be seen that the chromatographic resolution was improved by using Method 1 as shown in Figure 1. Figure 1a shows that when using the 100 minute HPLC method, there were many co-eluting peaks occurring between 12 and 22 minutes, while in Figure 1b, these peaks were better resolved using the UPLC technique.

The advantage of the improved resolution of Method 1 means that it is possible to use the UPLC method to monitor for known adulterations. As discussed in the Aim section, some common issues such as mistaken identity of fruits often occur. Figure 2 shows how easy it is to detect pear in apple juices, since there are several unique components associated with each fruit using UV detection. However, identification alone with UV in this example might lead to an incorrect assignment of the peak eluting at t_R 1.08 min in the apple sample as arbutin. Using the MS data, this was proven not to be the case and Table 4 shows that there is a high presence of arbutin in pear that is absent in the apple sample.

Figure 3 shows chlorogenic acid in another apple sample. The top chromatogram shows the data for UV and the bottom shows the same sample using MS. For both, the chromatograms the peak at t_R 4.63 min appears to be one peak.

However, the mass spectrum indicates the presence of two compounds, as shown in Figure 4. By using the MS data to quantify for chlorogenic acid, the result was more accurate than the result from the UV data. The use of the Waters ACQUITY SQD allows the analyst to perform a more comprehensive search for more subtle adulterations that may occur.

An additional advantage of the ACQUITY SQD is its ability to give fragmentation patterns associated to the compound, making it a very selective technique (see Figure 4). It is also possible to induce further fragmentation in-source, enabling the generation of more structurally significant ions that could assist with compound identification/elucidation.

The addition of the SQ Detector not only aids with correct quantification of peaks in the chromatogram (see Table 3), but also allows the throughput to be further increased. For quantification of the key compounds only, the run time was improved ten-fold using the ACQUITY UPLC System in Method 2. The mass selectivity of the ACQUITY SQD when compared with UV detection enables co-eluting peaks to be identified and quantified by their specific m/z.

Waters ACQUITY UPLC System with the SQ Detector affords a number of key benefits to the food testing QC laboratory, including:

• HPLC methods can be readily transferred to the UPLC platform.
• The UPLC method provides superior resolution and speed as compared to traditional HPLC techniques. This results in improved laboratory efficiency (through the reduction of sample analysis bottlenecks) as well as lower operational costs.
• By employing the SQ Detector with the ACQUITY UPLC, it is possible to obtain more information in less time.
• The ACQUITY SQD provides additional security when quantifying known compounds in routine QC sample analyses.
• From an investigatory perspective, the mass spectral information allows for the recognition of sample non-conformance, such as adulteration.

1. G Shui, Lai P. Leong. J Chrom A. 977: 89–96, 2002.
2. J Food Comp & Analysis. 17: 675–685, 2004.
3. Molecules. 12:679–693, 2007.
4. J Chrom A. 913: 387–395, 2001.
5. J Agric Food Chem. Vol 54, No 1, 2006.

Acknowledgements

Thanks to Teresa Corkum and Susan Martin of The Coca-Cola Company who have supported this work.